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Data warehouse ⇄ CRM

Databricks to Freshsales integration — real-time, two-way sync

Keep Databricks and Freshsales in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Databricks and Freshsales

Sync Freshsales into Databricks continuously and push warehouse results back onto CRM records, one two-way connection instead of two pipelines.

The CRM feeds the warehouse and the warehouse should feed the CRM: relationship data flows one way, and computed scores, segments, and customer context flow back. Most teams build the first half as a batch pipeline and never quite get to the second.

Stacksync does both with one connection. Deals, Tasks, Appointments, Notes from Freshsales land in Databricks as live tables, updated within seconds, and columns computed in Databricks write back to fields in Freshsales. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.

Common use cases

  • Sync sales activities and appointments into analytics tools for rep productivity reporting.
  • Two-way sync of contacts and accounts between Freshsales and a Postgres database so product and data teams query CRM data with SQL.
  • Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
  • Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.

Cleanup that sticks

Deduplication and normalization done in Databricks can be written back, so warehouse-side cleanup actually fixes the CRM.

CRM analytics on live data

Accounts, contacts, and activity from Freshsales are queryable in Databricks moments after they change, so dashboards stop lagging the reality they describe.

Scores and segments back on the record

Lead scores, churn risk, or usage segments computed in Databricks appear as fields in Freshsales, where the people working accounts actually see them.

What you can sync between Databricks and Freshsales

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Databricks objects Freshsales objects
Change Data Feed Row-level change records on Delta tables that drive incremental reads. Products Catalog items attached to deals for line-level revenue data.
Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. Contacts Person records carrying lifecycle stages; the main entity for two-way CRM syncs.
Schemas Group tables and views; syncs typically target a dedicated schema per source system. Accounts Company records kept aligned with billing, ERP, and warehouse tables.
Delta Tables The primary read and write target; operational data lands here as managed or external tables. Deals Pipeline records synced to a warehouse for revenue reporting.
Views Curated read-only projections used as sync sources for downstream tools. Tasks Rep to-dos created from external triggers or synced for productivity reporting.
Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. Appointments Scheduled meetings readable for activity analytics.
What ships with Databricks ⇄ Freshsales

Connect Databricks and Freshsales for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–Freshsales connection.

Real-time

Two-way sync

Changes in Databricks or Freshsales instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Freshsales data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Databricks or Freshsales record.

Observability

Monitoring

Track your Databricks ⇄ Freshsales sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Databricks and Freshsales.

How the Databricks and Freshsales connectors work

Databricks

Integration surface
SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution
Authentication
Personal access tokens or OAuth machine-to-machine credentials for service principals
Change detection
Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns
Capabilities
read · write · CDC
Rate limits
Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits

Freshsales

Integration surface
REST API
Authentication
API key sent as a Token authorization header
Change detection
Polling with updated-at filters through views; outbound webhooks can be configured via workflow automations
Capabilities
read · write · webhooks
Rate limits
Subject to per-account API rate limits that vary by Freshworks plan
How it works

How to connect Databricks to Freshsales — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Databricks and Freshsales with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Databricks connected
    Freshsales connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Databricks and Freshsales objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Databricks ⇄ Freshsales
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Databricks Freshsales
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Databricks and Freshsales integration FAQ

SECURITY

Security teams love Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

Learn more about security
SOC 2 type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 386 integrations available for Databricks and Freshsales.

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